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Partitioned Wild Bootstrap for Panel Data Quantile Regression
Antonio F. Galvao, Carlos Lamarche, Thomas Parker
Practical inference procedures for quantile regression models of panel data have been a pervasive concern in empirical work, and can be especially challenging when the panel is obs…
Estimation of a Factor-Augmented Linear Model with Applications Using Student Achievement Data
Matthew Harding, Carlos Lamarche, Chris Muris
In many longitudinal settings, economic theory does not guide practitioners on the type of restrictions that must be imposed to solve the rotational indeterminacy of factor-augment…
Wild Bootstrap Inference for Penalized Quantile Regression for Longitudinal Data
Carlos Lamarche, Thomas Parker
The existing theory of penalized quantile regression for longitudinal data has focused primarily on point estimation. In this work, we investigate statistical inference. We propose…
A Panel Quantile Approach to Attrition Bias in Big Data: Evidence from a Randomized Experiment
Matthew Harding, Carlos Lamarche
This paper introduces a quantile regression estimator for panel data models with individual heterogeneity and attrition. The method is motivated by the fact that attrition bias is…